Simple RAG Consumption with Pinecone

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Simple RAG Consumption with Pinecone recipe assets

The following table lists the assets that the Simple RAG Consumption with Pinecone recipe package contains:

Asset Name	Asset Type	Description
PineconeRAGConsumption	App connection	Pinecone connection.
GeminiRAGConsumption	App connection	Gemini connection.
VectorMatchEntry	Process object	Provides all the information from the Pinecone vector matching.
Get Gemini Embeddings	Process	Subprocess that creates embedding vectors from input text using Gemini AI.
Pinecone Upsert Embedding	Process	Subprocess that saves vectors to the Pinecone index.
Fill Empty Pinecone Index Using Gemini AI	Process	Subprocess that creates vectors using Gemini AI and saves them in an empty Pinecone index.
Generate Embeddings Model	Process	Subprocess that parses user input into a vector view and matches it with the embedding model. Returns the matching context score and metadata.
Query Pinecone	Process	Subprocess that searches coincidences from input vectors to vectors in the base Pinecone index specified as input parameter Index_Host_Pinecone. Returns a result with metadata.
Query LLM With Context (Gemini)	Process	Subprocess that prepares and sends requests to the Gemini LLM with the context.
Get Embeddings	Process	Subprocess that generates embedding vectors from the user input using Gemini.
Query LLM with Context using Embeddings Model	Process	Submits a query that is received from the user, converts it into a vector, and uses it to search for similar vectors in a database. The top K matches are retrieved, filtered by a cutoff score, and used to form a context. This context including the original query is passed to a Large Language Model (LLM) to generate and return a comprehensive response.